Paper Citation Record · LEDGER

Optimizing In Vivo Oral Lesion Classification from Electrical Impedance Spectroscopy Using Data-driven Approaches

As of 5 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2605.05729.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2605.05729 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-08T07:30:28.056678Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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Source: cited_works

Reference resolution

35 of 35 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 67503119-e7bf-4508-80c6-2be65aef256d · outbound

This paper cites Cancer statistics, 2025.

Optimizing In Vivo Oral Lesion Classification from Electrical Impedance Spectroscopy Using Data-driven Approaches Cancer statistics, 2025

Reference 1

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Source-reported events for the cited work

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Observation 09a7ff4c-f094-4306-89b9-9daca789c017 · outbound

This paper cites Cancer of the oral cavity and pharynx - cancer stat facts.

Optimizing In Vivo Oral Lesion Classification from Electrical Impedance Spectroscopy Using Data-driven Approaches Cancer of the oral cavity and pharynx - cancer stat facts

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T17:48:09.298332Z

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Observation 14c446ae-47c8-46a5-9eae-c9bc9544444e · outbound

This paper cites The pathology of oral cancer.

Optimizing In Vivo Oral Lesion Classification from Electrical Impedance Spectroscopy Using Data-driven Approaches The pathology of oral cancer

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T17:48:09.301505Z

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Observation 44eb44f8-27c0-44c5-952c-3c5bd39b2e47 · outbound

This paper cites Why oral histopathology suffers inter-observer variability on grading oral epithelial dysplasia: an attempt to understand the sources of variation.

Optimizing In Vivo Oral Lesion Classification from Electrical Impedance Spectroscopy Using Data-driven Approaches Why oral histopathology suffers inter-observer variability on grading oral epithelial dysplasia: an attempt to understand the sources of variation

Reference 4

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Observation 417b7ded-896c-4f53-9b2f-34b5a6819d5e · outbound

This paper cites Interobserver agreement in dysplasia grading: toward an enhanced gold standard for clinical pathology trials.

Optimizing In Vivo Oral Lesion Classification from Electrical Impedance Spectroscopy Using Data-driven Approaches Interobserver agreement in dysplasia grading: toward an enhanced gold standard for clinical pathology trials

Reference 5

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Observation eb075b43-131f-435b-8b9f-40aac3b0911e · outbound

This paper cites Experiences, perceptions, and decision-making capacity towards oral biopsy among dental students and dentists.

Optimizing In Vivo Oral Lesion Classification from Electrical Impedance Spectroscopy Using Data-driven Approaches Experiences, perceptions, and decision-making capacity towards oral biopsy among dental students and dentists

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T17:48:09.279986Z

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Observation 3c0f07c1-5980-4212-82e4-d0f11ad64d5a · outbound

This paper cites Optical fluorescence imag- ing in oral cancer and potentially malignant disorders: A systematic review.

Optimizing In Vivo Oral Lesion Classification from Electrical Impedance Spectroscopy Using Data-driven Approaches Optical fluorescence imag- ing in oral cancer and potentially malignant disorders: A systematic review

Reference 7

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Observation f0127a19-1a71-4bf5-8f4e-1756fb396c8f · outbound

This paper cites Understanding the biological basis of autofluores- cence imaging for oral cancer detection: high-resolution fluorescence microscopy in viable tissue.

Optimizing In Vivo Oral Lesion Classification from Electrical Impedance Spectroscopy Using Data-driven Approaches Understanding the biological basis of autofluores- cence imaging for oral cancer detection: high-resolution fluorescence microscopy in viable tissue

Reference 8

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Observation d9bd8007-235c-4e94-93ca-b7c2d972c316 · outbound

This paper cites Intraop- erative use of wide-field optical coherence tomography to evaluate tissue microstructure in the oral cavity and oropharynx.

Optimizing In Vivo Oral Lesion Classification from Electrical Impedance Spectroscopy Using Data-driven Approaches Intraop- erative use of wide-field optical coherence tomography to evaluate tissue microstructure in the oral cavity and oropharynx

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T17:48:09.283978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 41b8a03c-63ca-4b1c-a5f1-89ce694dbcf4 · outbound

This paper cites Technology review: The use of electrical impedance scanning in the detection of breast cancer.

Optimizing In Vivo Oral Lesion Classification from Electrical Impedance Spectroscopy Using Data-driven Approaches Technology review: The use of electrical impedance scanning in the detection of breast cancer

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T17:48:09.268713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 957555dd-eb04-4668-9ff7-e879292b26f7 · outbound

This paper cites Electrical impedance spectroscopy of the human prostate.

Optimizing In Vivo Oral Lesion Classification from Electrical Impedance Spectroscopy Using Data-driven Approaches Electrical impedance spectroscopy of the human prostate

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T17:48:09.271937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation f4de7292-ffd0-4e6f-a9a1-ddc83f6c1467 · outbound

This paper cites Use of electrical impedance spectroscopy to detect malig- nant and potentially malignant oral lesions.

Optimizing In Vivo Oral Lesion Classification from Electrical Impedance Spectroscopy Using Data-driven Approaches Use of electrical impedance spectroscopy to detect malig- nant and potentially malignant oral lesions

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T17:48:09.378913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 50084f35-3e4d-43ba-9ecd-1b3faa6d0295 · outbound

This paper cites In vivo classification of oral lesions using electrical impedance spectroscopy.

Optimizing In Vivo Oral Lesion Classification from Electrical Impedance Spectroscopy Using Data-driven Approaches In vivo classification of oral lesions using electrical impedance spectroscopy

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T17:48:09.382087Z

Source-reported events for the cited work

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Observation fc8fbb26-b94a-42a8-be15-4c1dc434b63f · outbound

This paper cites The use of bioimpedance in the detection/screening of tongue cancer.

Optimizing In Vivo Oral Lesion Classification from Electrical Impedance Spectroscopy Using Data-driven Approaches The use of bioimpedance in the detection/screening of tongue cancer

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T17:48:09.372254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 2446339b-92d8-4ae6-9e29-c16d6b686e3d · outbound

This paper cites A preliminary study of the use of bioimpedance in the screening of squamous tongue cancer.

Optimizing In Vivo Oral Lesion Classification from Electrical Impedance Spectroscopy Using Data-driven Approaches A preliminary study of the use of bioimpedance in the screening of squamous tongue cancer

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T17:48:09.355011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 426c311d-8ce9-44bd-a3e2-a79421bd103d · outbound

This paper cites Tissue level based deep learning framework for early detection of dysplasia in oral squamous epithelium.

Optimizing In Vivo Oral Lesion Classification from Electrical Impedance Spectroscopy Using Data-driven Approaches Tissue level based deep learning framework for early detection of dysplasia in oral squamous epithelium

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T17:48:09.358180Z

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation d6bcf332-f7d5-4f3b-8cbb-35d206140978 · outbound

This paper cites Computer-assisted medical image classification for early diagnosis of oral cancer employing deep learning algorithm.

Optimizing In Vivo Oral Lesion Classification from Electrical Impedance Spectroscopy Using Data-driven Approaches Computer-assisted medical image classification for early diagnosis of oral cancer employing deep learning algorithm

Reference 17

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Observation ecc2aa9a-2270-40af-bde4-0956a0c815c6 · outbound

This paper cites Automatic classification of cancerous tissue in laserendomicroscopy images of the oral cavity using deep learning.

Optimizing In Vivo Oral Lesion Classification from Electrical Impedance Spectroscopy Using Data-driven Approaches Automatic classification of cancerous tissue in laserendomicroscopy images of the oral cavity using deep learning

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T17:48:09.368873Z

Source-reported events for the cited work

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Observation 3a8f940e-9d8a-4710-82df-3a1be1907bab · outbound

This paper cites An early diagnosis of oral cancer based on three-dimensional convolutional neural networks.

Optimizing In Vivo Oral Lesion Classification from Electrical Impedance Spectroscopy Using Data-driven Approaches An early diagnosis of oral cancer based on three-dimensional convolutional neural networks

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T17:48:09.341505Z

Source-reported events for the cited work

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Observation 99c88a0c-3ea4-4b83-9bda-b2abb0172eed · outbound

This paper cites Deep learning-based electrical impedance spectroscopy analysis for malignant and potentially malignant oral disorder detection.

Optimizing In Vivo Oral Lesion Classification from Electrical Impedance Spectroscopy Using Data-driven Approaches Deep learning-based electrical impedance spectroscopy analysis for malignant and potentially malignant oral disorder detection

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T17:48:09.345447Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 79a03474-8464-447a-a3f3-b6172f26d6ac · outbound

This paper cites Electrical impedance-based tissue classification for bladder tumor differentiation.

Optimizing In Vivo Oral Lesion Classification from Electrical Impedance Spectroscopy Using Data-driven Approaches Electrical impedance-based tissue classification for bladder tumor differentiation

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T17:48:09.351948Z

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Observation ebff21d7-ffcb-44da-a08c-bf507293a71e · outbound

This paper cites IIVV Evaluation.

Optimizing In Vivo Oral Lesion Classification from Electrical Impedance Spectroscopy Using Data-driven Approaches IIVV Evaluation

Reference 22

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Observation 82133f2b-01d5-4a6b-b92b-5ce22bb3da54 · outbound

This paper cites A clinically feasible electrode array for 3d intraoperative electrical impedance tomography-based surgical margin assessment in robot-assisted radical prostatectomy.

Optimizing In Vivo Oral Lesion Classification from Electrical Impedance Spectroscopy Using Data-driven Approaches A clinically feasible electrode array for 3d intraoperative electrical impedance tomography-based surgical margin assessment in robot-assisted radical prostatectomy

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T17:48:09.331967Z

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Observation fdc255c5-e040-470b-9c4f-3d73e7e85379 · outbound

This paper cites Comparison of complex open domain electrical impedance tomography methods.

Optimizing In Vivo Oral Lesion Classification from Electrical Impedance Spectroscopy Using Data-driven Approaches Comparison of complex open domain electrical impedance tomography methods

Reference 24

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Observation d5611b8e-2eac-4c72-97fc-14e38b78ef4b · outbound

This paper cites Binary-and three-tiered oral epithelial dysplasia grading system and malignant transformation.

Optimizing In Vivo Oral Lesion Classification from Electrical Impedance Spectroscopy Using Data-driven Approaches Binary-and three-tiered oral epithelial dysplasia grading system and malignant transformation

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T17:48:09.335447Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation c6e0e4f8-eb45-4a66-a985-d67d996fe7d2 · outbound

This paper cites Oral epithelial dysplasia: Do we have a management solution? a systematic review.

Optimizing In Vivo Oral Lesion Classification from Electrical Impedance Spectroscopy Using Data-driven Approaches Oral epithelial dysplasia: Do we have a management solution? a systematic review

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T17:48:09.348528Z

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 52ffb732-2c02-4554-8381-c0cd45043232 · outbound

This paper cites Scikit-learn: Machine learning in Python.

Optimizing In Vivo Oral Lesion Classification from Electrical Impedance Spectroscopy Using Data-driven Approaches Scikit-learn: Machine learning in Python

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T17:48:09.365278Z

Source-reported events for the cited work

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Observation 4d119ec2-7e93-4df7-9445-cece3ceedeea · outbound

This paper cites Principal component analysis.

Optimizing In Vivo Oral Lesion Classification from Electrical Impedance Spectroscopy Using Data-driven Approaches Principal component analysis

Reference 28

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Observation f73e8ae8-619b-4d2d-a7de-2a613359af63 · outbound

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Optimizing In Vivo Oral Lesion Classification from Electrical Impedance Spectroscopy Using Data-driven Approaches Support-vector networks

Reference 29

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation ae8b8ed7-109c-4910-a51e-62e5ad998b49 · outbound

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Optimizing In Vivo Oral Lesion Classification from Electrical Impedance Spectroscopy Using Data-driven Approaches Support vector machines

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T17:48:09.311895Z

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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This paper cites Random forests.

Optimizing In Vivo Oral Lesion Classification from Electrical Impedance Spectroscopy Using Data-driven Approaches Random forests

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T17:48:09.315337Z

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Optimizing In Vivo Oral Lesion Classification from Electrical Impedance Spectroscopy Using Data-driven Approaches Unresolved cited work

Reference 32

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This paper cites The meaning and use of the area under a receiver operating characteristic (roc) curve.

Optimizing In Vivo Oral Lesion Classification from Electrical Impedance Spectroscopy Using Data-driven Approaches The meaning and use of the area under a receiver operating characteristic (roc) curve

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T17:48:09.318971Z

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 0f75abaf-351a-4433-800f-497dbc3fdbb8 · outbound

This paper cites Machine learning applications in cancer prognosis and prediction.

Optimizing In Vivo Oral Lesion Classification from Electrical Impedance Spectroscopy Using Data-driven Approaches Machine learning applications in cancer prognosis and prediction

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T17:48:09.308805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 3942f8e4-f50e-4ee7-be12-baac665ca286 · outbound

This paper cites Low-frequency dielectric properties of the oral mucosa.

Optimizing In Vivo Oral Lesion Classification from Electrical Impedance Spectroscopy Using Data-driven Approaches Low-frequency dielectric properties of the oral mucosa

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T17:48:09.305442Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Pith citing papers

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